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Overall Equipment Effectiveness (OEE) – A Practical Guide

OEE (overall equipment effectiveness) is one of the best measurements you can use to optimize production processes.

When talking about production at scale, minor improvements can give a significant boost to your bottom line. That is especially evident in the manufacturing industry where shaving off a few seconds on one production process or reducing the number of defects by just 1% can bring in tens of thousands of dollars every month.

Continue reading this article and learn how you can take full advantage of OEE  and maximize production output.  We discuss definitions, explain formulas, and give practical examples.

The basics of OEE

OEE stands for “Overall Equipment Effectiveness”. In short, OEE is a key performance indicator (KPI) that compares your equipment’s ideal performance to its real performance. 

It is a quantifiable (i.e., uses numbers) way to find out how well your equipment, people, and processes do their job by measuring:

  • available time/uptime (availability)
  • maintaining speed and consistency (performance)
  • producing few defects (quality)

OEE uses productivity data to find the percentage of good production time on an asset. That means that each piece of equipment gets its own OEE score. 

While scoring each machine may sound putzy, it is worth the effort. OEE measures the machine’s productivity, yes. But it also takes into account the humans that run them. You know as well as we do that machines aren’t always the problem. Staff and processes are just as likely to lower productivity. 

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Production utopia

Your new machines are in top working order and never break. Your staff is well-trained, never late, and never requires breaks. You only produce one kind of product on all shifts, ever. Once a process is set, it is followed 100% of the time. 

That kind of perfection is impossible (and it is also kind of creepy in that sci-fi sort of way). There will be changeovers and defects. There will be downtime, breakdowns, staff issues, and steps that get missed. A hot and humid day, which no one has control over, will make something – or someone – overheat. And those are just minor issues.

Since we know that 100% productivity is unreachable, how do you know when you’re doing enough? How much deviation from that sci-fi level of productivity is OK? And when you stray too far away from it, how do you even begin to get better?

All this is why OEE exists in the first place. You know that productivity will never be perfect. OEE gives you a way to assess how close your process is to the ideal. Not only that, but it also gives you direction on how to improve:

  • it helps you break down where issues happen so that you can fix them more easily 
  • it is a diagnostic tool for your production process
  • it quickly uncovers losses as well as highly productive areas
  • it helps nudge you ever closer to your highest level of productivity

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Tips for getting started with OEE

When starting with OEE, there are a few best practices you should follow to ensure your success.

Start from good

Overall equipment effectiveness takes your manufacturing program from good to great – so you need to be starting from “good.” This means:

If you are in Maintenance, these may not directly be part of your job. You must work with your production lines and managers. They will have access to the data you need and be partners for you in fixing issues once you find them.

You, in turn, will also be a partner to them. Your maintenance program must also be in a good place, with well-oiled PM and tools like Limble to help with data collection. 

Play the long-game

OEE can earn significant rewards. But many avoid it because of the effort it takes to track and gather the data you need over time. 

If you do mid-or large-scale manufacturing, you will be glad you gave it the time and effort. Saving two seconds here and three defects there will make a major impact on your bottom line. And once you make those improvements, the savings and efficiency you gain will only grow over time.

Track all the variables 

OEE measures the machine’s productivity, yes. But it also takes into account the humans that run them as well. 

You know as well as we do that machines are not always the problem. Staff and processes are just as likely to cause issues and reduce productivity. Gaining insights into all parts of your strategy is what OEE is all about, so you can:

  • Squeeze every drop out of your equipment
  • Reduce the number of defective products
  • Maximize workforce productivity
  • Reduce repair costs by noticing problems early
  • Eliminate wasteful steps in your production process
  • Reach production efficiency

Once you start on the path toward those improvements, you will be well on your way to a lean manufacturing process.

In large-scale production, you need to dig deeper to go further. 

[Tool: Machine Productivity Data Log]

Production processes



Key metrics for OEE

Before we dive into the math head-first, we need to grab a few key metrics. You can use this as a checklist to make sure you have what you need. For any that you are not currently measuring, you will need to work out a process to collect that data before beginning your OEE calculations.

To put it simply, the numbers you need will fall into two main categories: parts and time. 

Measuring the number of parts you have produced

  • Good count – the number of good parts (that meet quality standards the first time) made during a set period.
  • Total count – the number of all parts (including defects) made during a set period.
  • Defective count – The number of defective parts (rejected because they do not meet quality standards) made during a set period.

Measuring production time

We can measure:

  • Planned production time: Total time a piece of equipment is expected and scheduled to run.
  • Run time: The amount of time that a process is actually running. Run time does not include downtime but does include small stops, slowed production, or time spent addressing rejected parts. 
  • Stop time: The total amount of time production stopped due to both unplanned and planned stops. Planned stops are when production is stopped due to a planned event such as a changeover or make-ready event. Unplanned stops are when production is stopped due to an unplanned event such as a breakdown or material shortage.

Measuring your ideal productivity

In addition to those real-life numbers, you will need to have an ideal for comparison. Think back to the picture we painted a little earlier of 100% productivity. In that case, how many parts would you produce in an hour? How long would it take you to make one good part? 

Even though you will never achieve them, knowing what 100% productivity might look like is necessary if you want to know how close you are to it. Here are the ideal productivity measures you will need to set.

  • Ideal cycle time: the ideal time it takes to produce one part.
  • Ideal run rate: the maximum number of parts made in a minute under ideal conditions/at maximum productivity.
  • Net runtime: the fastest/ideal amount of time it would take to produce a specific number of parts. 

Ideals are hypothetical (i.e., they are made up). They must be high enough that you always have something to work toward. But not so high that it is not a relevant comparison.

So, the obvious question here is this: If all these ideal measurements are made up and impossible to achieve, how on earth do you know what they should be?

How do you set an ideal?

Base your ideals on the least amount of time it could take to make one part. To find that, you will have to work with your colleagues to consider the following:

  • Machine capacity
  • Production goals
  • Machine operators’ skill level
  • Scheduling issues or conflicts with other equipment
  • Quality and availability of materials

Work with other leaders to develop the ideal metrics that are right for you and your company.

How to calculate OEE

As we dive in, let’s set one ground rule for the numbers you’re using: always use the smallest unit of measurement you can. Otherwise, you will not be able to get to the correct OEE score. That means time will appear as seconds rather than minutes or hours. 

Let’s put that into practice and do a little math warm-up now to establish that there are 3,600 seconds in an hour. You’ll see that reflected in our examples below:

60 seconds in a minute x 60 minutes in an hour = 3600 seconds in an hour 

See? You can do this.

Simple OEE formula

If you are new to OEE or have an atypical production model or process, you may want to start with this. It uses fewer calculations to get to a score but doesn’t provide as much depth or detail. It goes like this:

OEE Performance calculation

Simply insert the numbers you collected for each item and plug them into this formula. You will then have a simple OEE score. Let’s walk through an example with real numbers.

  • The fastest your production system can make one part is 3 seconds per part. So, your ideal cycle time is 3.
  • Let’s also pretend that you need to make 4,000 of those parts. That makes your good count 4,000.
  • If you multiply one by the other, you’ll find that ideally, it should take you about 12,000 seconds to make those 4,000 parts. If we do a little more math, 12,000 seconds comes to 3 hours and 20 minutes for those 4,000 parts, provided there are no interruptions, defects, etc. 
  • Your shift is 18,000 seconds long (or 5 hours). This is your planned production time. 
  • If you divide 12,000 by 18,000, you get .667. 
  • Convert that to a percentage (i.e., move the decimal two places to the left and add a %), and you find that you are running at about 66.7% OEE.

Let’s review in formula format:

(ideal cycle time of 3 seconds x good count of 4,000) / planned production time of 18,000 seconds = 66.7%

Now, let’s say that 500 of the 4,000 products we made were defective. How does that impact our OEE score with this calculation?

(ideal cycle time of 3 seconds x good count of 3,500) / planned production time of 18,000 seconds = 58.3% 

That’s quite a difference!

Although this is an acceptable calculation of OEE, it doesn’t give us enough insight to know what we need to change if we want to improve it. For that, we need to use the advanced version of this calculation.

Advanced OEE formula

The full-on OEE score involves three numbers, and each one takes a little math to get to on their own. It is not hard, but there are a few steps involved, so if you are reading this on a Monday morning, let’s grab one more cup of coffee and get to it.


Availability is the amount of time that your equipment or process is running as it should. It is the percentage of your planned production time that was spent producing (run time). Here is the formula for that:

OEE Availability calculation

Using our example from above, even though our planned production time was a 5-hour shift (18,000 seconds), production stopped for 45 minutes (2,700 seconds) due to a breakdown. That gives us a run time of 15,300 seconds. 

15,300 Run time / 18,000 Planned production time = .85

Divide 15,300 by 18,000 and do our decimal place magic, and we get an availability score of 85%. This is the first number in our advanced OEE score.


This is the speed of your production process and your ability to stay at that pace over time. It is the percentage of how close your run time was to the ideal.

OEE Performance calculation

In our example above, we know that it would take 3 seconds to make one part under perfect conditions. Making 4,000 parts should take 12,000 seconds. Given that our actual run time to make that amount was 17,100 seconds, our math will look like this:

(3 seconds Ideal cycle time x 4,000 Total Count) / 15,300 Run Time = .784

That is a performance score of 78.4%. Not bad!


Quality refers to, well, the quality of parts and how often you make defects. And this one is pretty easy. It is the percentage of all parts you made that met your quality standards (good).

OEE Quality calculation

Using our example here, we know that of the total parts we made (4,000), 3,500 met our standards. So…

3,500 Good parts / 4,000 Total parts = .875

That’s a quality score of 87.5%.

Your final OEE

We are entering the home stretch now! We have our availability, performance, and quality scores. Let’s combine them to get our final OEE. 

final oee

.85 Availability x .784 Performance x .875 Quality = .583

Congratulations. You made it! You have an OEE score of 58.3%

That’s great! 

…Isn’t it? Or is it not that great? Or somewhere in between? How do we know? We have our OEE score, and now we need a little context. Luckily, there is a lot of research to help you interpret your score and compare it to industry standards. Onward!

Understanding your OEE rating

Now that you have your bright and shiny new OEE score let’s figure out what it means and how it compares to others.

First baseline

Before starting on the path to continuous improvement and lean manufacturing, it is important to be clear about the scope of your rating. If this is your first OEE score, it will serve as your baseline, the benchmark to which you compare all future scores. 

It will be the starting point for comparing future OEE scores and measuring improvements. As you make those improvements and comparisons, keep in mind:

  • How much data did you include in this baseline? Measurement over a longer period gives a more accurate score.
  • What part of the production process was included? Consider comparing OEE scores of different shifts or machines.

What the number itself means

OEE scores are always percentages no matter what they are measuring. They were designed this way so that they are easier to compare. This helps you know how your OEE stacks up to others – both inside and outside your company.

eoo benchmark

We can see that an OEE of 85% is world-class performance. A score of 60% is very common and implies that there is room for substantial improvement. And 40% OEE is typical for those just starting the process of tracking and continuous improvement. 

We now know that our score from above of 58.3% OEE is pretty average – not bad, not great – and that we have some good room for improvement. 

The key here is that getting your OEE score is just the beginning, regardless of your score and how it compares to others. Your OEE can not only tell you where you stand, but it can also tell you what direction to go in to improve.

The Six Big Losses

OEE is not the car that will drive improvement at your organization – you are. But OEE does provide the road map to get you where you want to go. 

The road to get to your OEE score may feel long and littered with mathematical twists and turns. The truth is, those twists and turns – each number and formula you used – clearly tell you how to improve. 

This is the real goal of OEE – to help you address the “Six Big Losses.” The Six Big Losses are the problems that most commonly cause inefficiency and waste in manufacturing. They fall into three groups and – surprise! – you already know what they are:

  • Availability Losses
  • Performance Losses
  • Quality Losses

oee six big losses

The Six Big Losses. Source: OEE.com

Next, we’ll go through all three categories, tell you what the six big losses are, and how to address them. Because they all feed directly into your OEE score, you’ll see your OEE score rise over time as you fix them.

How to reduce Availability losses 

The first two of the six big losses fall under your score and have to do with keeping your process up and running as much as possible. If your availability score is low, dig into your run time and plan production time numbers.

OEE losses

Schedule loss is not taken into account for OEE calculations as there is no point in measuring OEE at times when production isn’t even supposed to run. Schedule loss is used for calculating TEEP (Total Effective Equipment Performance).

Big Loss #1: Equipment breakdowns (unplanned downtime)

Equipment breakdowns are your most significant source of unplanned stops and idling. If unplanned downtime is what is dragging down your operating time, this is where you need to start. 

The solutions are:

  •  Implement an easy-to-use CMMS like Limble. It will help you make the most of your PM, reduce breakdowns, and maximize equipment performance.
  • Track your downtime. Most CMMS solutions have modules for tracking shutdowns and their reasons. Limble makes this simple with Custom Dashboards that allow you to pull reports on equipment problems automatically. They help you identify the biggest issues, so you can either repair or replace them at the right time.
  • Forecast and implement measures to prevent shutdowns. Once you find patterns in your downtime, you can avoid them. If a piece of equipment breaks down after a certain period of run time, plan your shifts around that until you have a more long-term fix.

Big Loss #2: Setup and adjustments (planned downtime)

Equipment setups and adjustments take time. There is no getting away from them. The good news is that they give us room to improve. Do them at the right time – in the right way – to minimize production losses. 

Here is how to reduce the frequency and length of these planned stops: 

  • Bigger batches mean fewer batches – and fewer equipment changes on your shop floor. If you can closely predict the total units you eventually need, you can plan your production much more efficiently. (If you are using a continuous production system, you won’t have to think about this.)
  • Implement Single-Minute Exchange of Die (SMED) technique. The SMED technique is a principle of lean production. Take a close look at what happens during your planned stops. Look for ways to eliminate or shorten steps. Your goal is to perform stops as quickly as possible – as close to one or single-digit minutes as you can.

How to reduce Performance losses

The next two of the six big losses fall under your performance score and have to do with, in short, speed. Addressing these two losses helps you maximize your production.

If your performance score is low, look into the consistency of your run time and cycle time numbers. 

Big Loss #3: Minor stoppage

Minor stops are hard to monitor and can seem unimportant. The truth is, many little stops happening in a large-scale manufacturing process add up quickly. Here is where to start.

Address deviations in real-time

Train machine operators to fix more minor issues on the spot. This is the foundation for autonomous maintenance and saves a lot of time. Your maintenance team is freed up for more serious breakdowns, and your production team doesn’t need to wait to fix a minor breakdown. 

If you have a CMMS like Limble, you have an excellent tool at your disposal to start AM. By giving them access to Limble, they can have all the help and instruction they need at their fingertips.
Track patterns of performance loss

When are minor stops or slow cycles most likely to happen? Patterns in this data can help you find and prevent the root cause. 

  • Does production go down during a particular shift? 
  • After routine maintenance? 
  • After a certain amount of run time?

Standardize processes

There is a reason SOPs exist. They are usually well-researched and thoroughly tested. We’ve said it before, and we’ll say it again: Follow the same process, every time. This leads to fewer mistakes and minor stops and is why many organizations work toward process automation whenever they can.

Big Loss #4: Reduced speed

Optimize your production cycle and speed
Reduced speed is nearly always the result of wear and tear, poor maintenance, or misuse. This is one area where we humans can relate. As we get older, we tend to get a bit slower. But if we have a good workout regimen and take care of ourselves, we can keep plugging along at a good pace for a long, long time. 

Do the same for your equipment. Keeping it in tip-top shape is the best thing you can do to help it maintain its production speed. Do what you need to do to shore up your PM program. Train your machine operators to use the equipment properly and take care of it. Give it a name and buy it flowers if you want to. The point is, treat it well. 

How to reduce Quality losses

A Quality rating of less than 100% means your production process results in some defective goods. 

The lower the quality score, the higher the percentage of defects. Look at the production processes and equipment in places where your quality score is lowest. 

Big Loss #5: Product scrap

Most defects are the result of deterioration in your equipment. Track the types of defects you see and closely monitor aging equipment. 

You may have a highly skilled maintenance team that can keep equipment running. But there will come a time when the reduced speed and amount of defects and rework will not be worth keeping the asset online. It will simply make more sense to replace it. 

Big Loss #6: Startup scrap

Reduce startup production

It is easy to get excited when you finally replace old equipment. The old one may have been so slow and inefficient for so long that you feel like you have to make up for lost time. 

Resist the urge to kick it into high gear right away. It may take a few batches before the product meets your quality standards. In the meantime, stick to smaller batches. It will allow you to find and fix problems before running full steam, saving you wasted time and materials.

Reduce quality variation 

Once the new equipment is set up and running well, don’t assume it will stay that way. Settings find ways of shifting, and materials change over time. Check both often in the early days so that you can resolve any changes quickly. 

Tracking and training for OEE

Tracking and training are both vital elements of any manufacturing process worth its salt. If your organization lacks either one, you may find it challenging to put OEE in place. 

Make sure your organization understands the value of these two topics and gives the resources needed for them to be done well. Limble CMMS is easy to use and tracks all kinds of data. It also offers templates and checklists for maintenance staff and maintenance operators to support your training programs.

Implementing OEE at your organization

It is always a good idea to pilot any major process changes. Pilots help you find and fix problems before they cause problems all over the place. They also help you understand how these changes will impact your organization. OEE is no different.

  • Define the scope of your pilot. Select a production area, piece of equipment, or team that is eager to improve. This will be your pilot group.
  • Determine the timeframe for initial data collection. Define a timeline for data collection, OEE analysis, and implementation of change. As we talked about earlier, it is essential to collect enough data – and the right data – to develop an accurate OEE score. Follow the definitions of each metric closely.
  • Analyze and improve. Once you have the data you need, perform your OEE calculations. Pinpoint the scores that can be improved. Review the six big losses above and choose one or two to address.
  • Analyze again. After you have put changes in place, continue your data collection. Reassess your OEE and see how it has changed.

Once your pilot is over, adjust your process based on what you have learned, if necessary. Then, apply it broadly. Remember that data collection is constant, and CI is never done.

For that reason, your data collection processes must be automated or built-in to day-to-day functions. Soon, you will have your first organization-wide OEE score!

Common OEE mistakes and how to avoid them

Overall Equipment Effectiveness can take your manufacturing process to the next level. However, if not done correctly, you may not reap the full benefits. Here are some of the most common mistakes with OEE.

1) Focusing on the OEE score, not the losses 

Keep in mind that OEE is a means to an end – not the end itself. It is a tool you can use to help measure your progress along a longer and more meaningful path to improvement. It is a point in time measurement and will not change unless you focus on improvement. 

Just like your bank account balance, you can stare at that number all day long, and it won’t get any bigger until you roll up your sleeves, get to work, and earn a paycheck. OEE is an easy way to measure where you are at any given point. But if you want to improve, the real focus must be on the losses and the steps you take to minimize them. 

2) Using OEE to compare unrelated processes and plants

Going from 0 to 60 MPH in 3 seconds in a Ferrari is expected – that’s what it was built for. But doing the same thing in your Toyota Prius is downright impossible. They are different machines with very (very) different purposes. Comparing them minimizes the value of both vehicles.

It is hard not to compare the many OEE scores across your organization but do so with caution. You must consider each individual process to determine why they may be producing – and why they may always produce – different OEE scores.

It is a mistake to compare dissimilar manufacturing operations because it places too much importance on the OEE score. And didn’t we warn you about that in the previous section? Remember that what you should be focusing on is the improvements you are making to minimize losses. 

3) Excluding changeovers in your OEE calculation

Yes, changeovers cost production time. There is no way around it. But they are also essential parts of your business and ripe areas for improvement. 

It is tempting to take them out of your time measurements because they make such a big difference. But not only does that minimize the accuracy of your score, but it also deprives you of one of your most profitable opportunities for improvement. 

4) Implementing OEE across the whole plant 

Woah there, Nelly. It can be exciting to have a tool that boils down your productivity into one easy-to-understand number. If you’re the kind of person who doesn’t like to do anything halfway, you may be eager to use it everywhere right out of the gates. 

Remember that it does take a good amount of time and effort to do it correctly. So use those resources carefully. By piloting the program, you can find areas where OEE will be most helpful and those where it will not.

5) Your data collection is too slow

Data collection that drags on and on runs the risk of spanning changes in process, staff, seasons, etc. All these things can mess with your data and make it hard to know what exactly needs improvement.

Collect data thoroughly and swiftly so that you obtain a score that truly represents your production process. Using CMMS and other cloud-based technology helps immensely as the data collection process can be largely automated.

6) Doing OEE “your way”

OEE is most valuable when compared across similar teams, production lines, and even similar organizations and industries. But, when you change the rules and calculate OEE in your way, you lose the ability to compare yourself to others. In addition, you lose the benefit of quickly finding and making improvements.

You’re in the Major Leagues now

Excellent maintenance and manufacturing teams practice consistency, leverage the right tools, and use best practices for continuous improvement. 

They also take every opportunity they can to reduce waste and use as few resources as possible. OEE is an excellent tool for this because it helps you:

  • Collect valuable data on maintenance operations and production, helping you take a big-picture approach.
  • Use proven assessments and analysis to peel back the layers and uncover ways to improve.

Limble is your partner in OEE and many other efficiency strategies. We offer an easy-to-use platform that enables each step in the OEE process. You can start a free trial here, request a demo, or even try out our online self-demo.

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